Evolution of the layers in a subsumption architecture robot controller

Abstract

An approach to robotics called layered evolution and merging features from the subsumption architecture into evolutionary robotics is presented, its advantages and its relevance for science and engineering are discussed. This approach is used to construct a layered controller for a simulated robot that learns which light source to approach in an environment with obstacles. The evolvability and performance of layered evolution on this task is compared to (standard) monolithic evolution, incremental and modularised evolution. To test the optimality of the evolved solutions the evolved controller is merged back into a single network. On the grounds of the test results, it is argued that layered evolution provides a superior approach for many tasks, and future research projects involving this approach are suggested.

References in Article

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Nolfi, S. (2002). Evolving robots able to self-localize in the environment: the importance of viewing cognition as the result of processes occuring at different time scales. Connection Science (14) 3:231-244.